Today's health practitioners are encouraged to diagnose and treat patients based on individual genetic composition. Pharmacogenomics promises to establish how genetic variation affects the way individuals will respond to drugs. Translation of this information into clinical settings would provide physicians the tools for selecting an optimal treatment for individual patients. Importantly, differences in drug responses caused by genetic differences among individuals could be correlated or quantified by diagnostic testing of an individual prior to receiving a particular drug or amount. The drug and amount could thus be tailored to the individual. Biomarker tests are currently based on polymorphic alleles at the genetic and protein level. For example, Oncotype DX is a commercially available test that predicts breast cancer recurrence and is used as a treatment guide for chemotherapy for breast cancer.
Pharmacogenomics research focuses primarily on establishing correlations between microarray gene expression profiles and disease states, often without defining biochemical pathways and mechanisms. This strategy is widely adopted, easy to automate, and scalable to high-throughput modes. However, the reliability of microarray biomarker assays for disease is unknown with few effective biomarkers or tools for assessment established. For example, only one assessment has begun to be used in oncology practice.
Efforts to identify cancer biomarkers through genomic methods have included use of microarray assays to mine for genetic predictors of therapeutic response and to mine for variations in tumor gene expression in patients whose disease later exhibits different degrees of aggressive behavior. These biomarkers are defined not by classical single markers, but by sets of genes whose up- or down-regulation in expression is correlated with a therapeutic response or aggressive behavior of the disease. Many of the gene signatures generated in the last five years for predicting disease have had only marginal overlap with those identified in the original studies, even though subsequent work had corroborated pathway mechanisms in the model organism studies. For example, BCR-ABL kinase domain mutations have been found to confer resistance to the tyrosine kinase inhibitor imatinib, a competitive inhibitor for the substrate ATP (60,61,62). As used herein and in the claims, a “drug” or “drug compound” is a therapeutic compound that is given to a patient that targets a specific protein.
Minimizing problems of validity, reproducibility, and bias in biomarker generation and employment is imperative when searching for predictors of therapeutic response. There is a need for standardization in methods and technology platforms to define biomarkers for predicting disease progression as well as predicting response. The interaction of a targeted protein and its inhibitor drug can be useful. In particular, certain enzymes such as ATPases and kinases that use ATP as a substrate have showed potential as targets for drugs. ATPases are enzymes that use ATP hydrolysis to achieve a cellular function, and are involved in various human diseases. Kinases will transfer the phosphate group in ATP to another compound. As such, ATPases and kinases are important protein targets for therapeutic drugs. In the ATPases, most of the drugs have inhibited activity by binding to an allosteric site. Examples include, Kinesin (Eg5) and its inhibitor monastrol used for cancer therapy; muscle myosin II and its inhibitor N-benzyl-p-toluene sulphonamide used for muscle relaxation; Na+,K+-ATPase and the inhibitor digoxin used for heart failure; P glycoprotein and its inhibitor XR9576 used for cancer, H+,K+-pump and its inhibitor benzimidazoles used for gastric ulcers; vacuolar H+-ATPase and the inhibitor bafilomycin Al used for osteroporosis; and DNA topoisomerase II and the inhibitor ICRF-193 used for cancer (59).
Allostery is important in controlled catalysis, signal transduction, and apoptosis (1). The classic view of proteins demonstrating this property (2) asserts that binding of a ligand at one site provokes conformational changes at a remote, second site. Recent studies (3) evaluating underlying mechanisms of allostery alternatively suggest that ligand binding results in selection of pre-existing conformational substrates. Implicit in the latter model, interactions between the orthosteric and allosteric sites are tightly linked through structure and thermodynamics (4).
The human Kinesin-5 motor protein (Eg5 or KSP) plays key roles in bipolar mitotic spindle formation and is a protein target for allosteric compounds (5-7) that alter catalytic ATPase activity of the protein (8,9). There are many compounds and classes of compounds that are know to inhibit KSP including monastrol, S-trityl-L-cysteine and its derivatives, quinazolines (e.g., ispinesib), adociasulfates, thetrahydroishquinolines, dihydropyrazoles, thiophenes, pyrrolotriazines, thiazoles, gossypol, indoles, and biphenyls. The best-characterized inhibitors, monastrol (10) and S-trityl-L-cysteine [STC; (9)], were uncovered from independent chemical screens. Biochemical studies demonstrate a wide concentration range of inhibition by these compounds (10-12) differences in the kinetic mechanism of allostery (13-15), and even allosteric activation (16) is possible.
Interest in these allosteric compounds, monastrol and STC, has been acute as they are potential anticancer agents. Additionally, these compounds serve as research tools to probe the fundamental mechanism by which Eg5, and perhaps all other motor proteins, convert and transduce energy to conformational changes in distal regions of the protein. Insights concerning allosteric conformational states of Eg5 result principally from diffraction- and microscopy-based techniques. The kinesin motor domain is an arrowhead-shaped structure with a central β-sheet flanked by 3 helices on each side. In crystallographic studies of Eg5·ADP complexed with monastrol (17,18) and other allosteric inhibitors (12,19-21), the wildtype Kinesin-5 motor domain displays a similar conformer, irrespective of the chemical nature of the allosteric drug.
The most notable conformational change observed is the adoption of a ‘closed’ conformation by the insertion loop (L5) of α2 helix that cradles the allosteric compound. This is in contrast with the ‘open’ conformation observed in the absence (22) of an allosteric ligand. However, conformational transitions of the L5 loop are found not only in response to drug binding, but also in normal motor function. The Eg5 conformer trapped by allosteric agents is suggested to be an intermediate state of its normal ATP hydrolysis cycle (23). The L5 loop is observed in the ‘closed’ conformation in cryo-EM experiments (24) with a D. melanogaster homologue of Eg5 bound to microtubules using non-hydrolyzable substrate analogues and in Eg5·AMPPNP crystals in the absence of allosteric agents (25).
No consensus of L5 residues key for transmitting allosteric information has been established, primarily due to interdependence of the allosteric and active-site interactions and the lack of rapid methods to observe structures of mutant motor proteins. Simple sequence conservation analysis does not reveal how the L5 loop specifically recognizes and binds an allosteric molecule. Studies (15,17,26,27) using targeted mutagenesis to measure the contribution of specific contacts in Eg5 allostery and chemical-kinetic measurements of mutant motor ensembles in solution on the whole concluded that their data were consistent with the crystallographic observation of the wildtype Eg5·inhibitor complexes. Yet, neither these reports nor X-ray structural analyses of allosterically-inhibited Eg5 proteins arrive at a common set of contact residues for binding many different chemical partners.
The advent of the structural genomics era has led to the curation of many motor protein structures; to date, 20 RCSB Protein Data Bank (PDB) entries for wildtype Eg5 alone have been deposited. (See the website: www dot rcsb dot org/pdb/home/home dot do) Although the atomic level detail of the structures is fairly complete, whether these static ‘snapshots’ accurately reflect functional states that these amino acid assemblies can achieve is more difficult to determine. Thus, obtaining all needed conformational possibilities in kinesin mechanotransduction and its allosteric inhibition is a significant challenge.